The proposed geographic information system-based study of the causes of childhood leukemia is not only designed to advance the state-of-the-art in epidemiologic methods, but also to lead to greater understanding of the etiologic role of environmental pollutants. The study employs an innovative application of GIS analytic capability to address some of the fundamental shortcomings of traditional epidemiology. It will build on one of the first large-scale GIS studies of patterns of childhood cancer, and one of the most extensive case-control studies of childhood leukemia undertaken in the US. As such, it represents an important direction in the evolution of GIS as an analysis tool. A key objective is to solve the problem of characterizing the spectrum of exposure opportunity to individuals, especially for the range of chemical agents potentially encountered in residential settings from environmental sources. The proposed study is organized around the hypothesis that perinatal or early life exposures to environmental chemicals are associated with increased risk of developing childhood leukemia. Primary exposure sources of concern for this project include agricultural pesticides, motor vehicle emissions, and other sources of air toxicants. The project will create individualized geographically-based estimates of exposure constructed from residential and school history data collected in the first five years of an ongoing UC Berkeley/California Department of Health Services case-control study, calibrated by measured air monitoring data and validated by means of laboratory analyses of household dust and air samples. These exposure estimates will be applied to the full case-control study (an estimated total of 660 cases and 1052 controls accessioned by year-2 of this project) to assess risk relationships, with adjustment for important covariables. The study offers sufficient power to detect even modest changes in environmental risk factors associated with the chemical agents of concern. The proposed project presents an unusual opportunity to extend the capabilities of GIS tools to assist epidemiologists in attributing population exposures, to validate generated exposure attributes, and to integrate these estimates with individual measures for a more comprehensive assessment of the role of environmental risk factors in the etiology of these little understood diseases.